1) Graduate School of Agricultural Science, Kobe University
2) Technical Section, Kitai Planning
3) Research Department, Research Institute for Humanity and Nature
4) Institute of Agriculture and Environment, Massey University, New Zealand

We developed an improved method to detect rice cultivated areas in semi-arid regions by combining the usage of Landsat imagery for detecting rice fields and MODIS for spatial and temporal upscaling of rice cultivation areas. We selected Haryana State in northwestern India as a case study area, where average farm plot size is small (~4,000 m2) and cultivated areas largely fluctuate from year to year due to water availability. Firstly, rice cultivated areas were detected by unsupervised classification of Landsat images of a specific year. Secondly, two conditional parameters for time-series EVI and LSWI were optimized by Powell’s method to best match the rice cultivated areas detected by MODIS to the areas detected by Landsat. Thirdly, calculated rice cultivated areas were compared with statistical data. Until results showed reasonable agreement, rice cultivated areas were reclassified in Landsat images and the following procedures were repeated. A good coefficient of determination (R2 = 0.82) was obtained between the estimated rice area and the statistical data at the district (sub-state) level in the study area. This demonstrates the potential and increased accuracy of the developed methodology to detect and map harvested rice areas in water scarce arid and semi-arid regions.